深層学習:Deep Learning

アルゴリズム:Algorithms

Protected: Machine Translation Today and Tomorrow – Different Machine Learning Approaches for Natural Language

Present and future of machine translation for digital transformation, artificial intelligence, and machine learning tasks - Different machine learning approaches for natural language machine translation based on attentional neural nets, machine translation based on encoding and decoding, recurrent neural nets, machine translation based on neural nets and neural models, neural net-based translation, tree-to-strong translation, pre-ordering, parse trees and parsing, word mapping, phrase-based translation
アルゴリズム:Algorithms

Protected: Equivalence of neural networks (deep learning) and Gaussian processes

On the equivalence of Gaussian processes and neural networks, an applied model of stochastic generative models used in digital transformation, artificial intelligence, and machine learning tasks from Neal's paper
アルゴリズム:Algorithms

Protected: Overviews of reinforcement learning and implementation of a simple MDP model

Overview of reinforcement learning used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks and implementation of a simple MDP model in python
アルゴリズム:Algorithms

Protected: Overview and history of the banded problem and its relationship to reinforcement learning/online learning

Overview and history of bandit problems utilized in digital transformation, artificial intelligence, and machine learning tasks and their relationship to reinforcement learning online learning
アルゴリズム:Algorithms

Protected: Meta-analysis in Medical Research Methods of Evidence Integration in Scientific Evidence-Based Medicine

Evidence integration in meta-analysis in science-based medicine as statistical data processing in digital transformation, artificial intelligence, and machine learning tasks method of moments, maximum likelihood, large sample theory, DerSimonian an Laird estimation, publication bias, network meta-analysis
グラフ理論

Optimization for the First Time Reading Notes

Optimization for the First Time Reading Notes From Optimization for Beginners This book is explained in d...
IOT技術:IOT Technology

Protected: Reconstructing the shape of celestial objects from time series data – Temporal Astronomy

Reconstruct the shape of celestial objects (V455 Andromeda, accretion disk structure, white dwarf) from time series data using Bayesian inference.
アルゴリズム:Algorithms

Dreams, Brain and Machine Learning From Dream Theory to Dream Data Science

Confirmation of dream experience in sleep (REM and non-REM sleep) using dream theory (Freud, Hobson activation-synthesis hypothesis, Ripley, etc.), brain networks and fMRI and machine learning (support Vectonema machine, Bayesian linear model with sparsity introduced)
LISP

Genetic Programming Theory and Practice X Papers

Artificial Intelligence Technology  Semantic Web Technology  Knowledge Information Processing Technology  Reasoning Tech...
アルゴリズム:Algorithms

Protected: Non-parametric Bayesian and clustering(1)Dirichlet distribution and infinite mixture Gaussian model

Analysis with a mixed Gaussian model that extends the Dirichlet distribution to infinite dimensions as a nonparametric Bayesian approach in stochastic generative models used in digital transformation artificial intelligence, and machine learning
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